Lancey VS Experimently

Let’s have a side-by-side comparison of Lancey vs Experimently to find out which one is better. This software comparison between Lancey and Experimently is based on genuine user reviews. Compare software prices, features, support, ease of use, and user reviews to make the best choice between these, and decide whether Lancey or Experimently fits your business.

Lancey

Lancey
Learn More | Visit Site
Lancey: Parallel AI agents turn customer feedback into production-ready code for engineering teams. Eliminate bottlenecks & ship fixes 10x faster.

Experimently

Experimently
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Rapidly create AI-powered, A/B tested landing pages with built-in lead forms. Experimently helps you validate ideas & optimize campaigns fast.

Lancey

Launched 2022-10
Pricing Model Free Trial
Starting Price
Tech used Framer,Amazon AWS CloudFront,unpkg,Google Fonts,HSTS
Tag A/B Testing,Growth Hacking

Experimently

Launched 2025-08
Pricing Model Freemium
Starting Price $19 / mo
Tech used
Tag

Lancey Rank/Visit

Global Rank 5303592
Country United States
Month Visit 2874

Top 5 Countries

100%
United States

Traffic Sources

17.59%
0.98%
0.04%
11.47%
25.79%
44.13%
social paidReferrals mail referrals search direct

Experimently Rank/Visit

Global Rank
Country
Month Visit

Top 5 Countries

Traffic Sources

Estimated traffic data from Similarweb

What are some alternatives?

When comparing Lancey and Experimently , you can also consider the following products

Engine - Engine is a remote AI software engineering agent that works with all of your tools and runs on any frontier LLM

Auto Claude - Autonomous multi-agent coding framework that plans, builds, and validates software for you.

Propel - Propel reviews pull requests by understanding your architecture, codebase, and policies. So senior engineers stay focused on the changes that matter.

Cosine - Cosine AI: Your autonomous agentic AI software engineer. Automate complex coding tasks, accelerate development & clear backlogs in production.

TaskingAI - TaskingAI brings Firebase's simplicity to AI-native app development. Start your project by selecting an LLM model, build a responsive assistant supported by stateful APIs, and enhance its capabilities with managed memory, tool integrations, and augmented generation system.

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